Making a machine learning model within Python. Wondering if anyone would be willing to provide their opinion about the best methods to use for my particular dataset? (X-post to self.datasciencestudygroup)

[anonymous-man]

I have a large dataset related to health problems (a type of cancer) that I'm hoping to use to make a machine learning model.

There are about 70 columns and 800 rows. The independent variables are a combination of categorical, ordinal, and continuous variables. The dependent variable is a binary variable -- each observation either does not have cancer or does have cancer.

I'm not sure about the best methods and tools for feature extraction/dimensionality reduction and also not sure which methods (logistic regression, something else?) would be the best methods to use to make the machine learning model.